Medical images are typically grey scale images wherein pixels are assigned a grey value between white and black. Various tissue components such as bone, cartilage, fat or organs in the image can be distinguishable by their “grey value” or relative intensity. For various medical procedures, accurate identification of the boundaries between the various tissue components (segmentation) of a medical image is required. Conventional methods for identification of the boundaries of tissue components involve use of manual identification of a number of points near a tissue boundary, at least one imaged tissue component of the medical image or a specific tissue region of interest in the image. Manual identification of the boundaries involves a person, e.g. a doctor or a medical technician, examining each image and manually inputting what they think are the boundaries of the bones in the image. The boundaries identified are input into a computer system which then analyzes the remaining portions of the image. The input typically consists of the technician or doctor assigning a grey value or threshold level of intensity to signify bone versus non-bone portions of the image.
It is often difficult or time consuming to segment bones in medical images, especially if there are multiple images. In addition to the differing thresholds applied by various technicians or doctors, as bones age, they undergo a process of mineralization that increases the density of the bone. Thus, younger bones have a different image appearance than the older bones of an adult animal or human patient. Conventionally, the images including bone segments are segmented by use of a threshold grey scale value, commonly referred to as a global threshold. The threshold grey scale value can be used to segment bone because typically bone will be displayed on a medical image with the greatest grey scale values. Pixels with a grey scale value above the threshold can thus be considered to be bone and pixels with a grey scale value below the threshold can be considered to something other than bone, such as cartilage or a space between the bones. Problems with segmentation of bone occur due to variability and the age of bones. The same grey scale value can not be suitable for every image. To overcome these problems, grey scale threshold values can be subjectively chosen by the user for input and interpretation of the image based at least upon the experience of the user. Being subjective, though, introduces variability not only between the images analyzed by a technician or doctor but also between images analyzed amongst more than one doctor or technician. This variability of the threshold creates errors in the determination of the boundaries.